Open AccessJournal Article
Design Considerations for Solar Energy Harvesting Wireless Embedded Systems
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In this article, the authors describe key issues and tradeoffs which arise in the design of solar energy harvesting, wireless embedded systems and present the design, implementation, and performance evaluation of Heliomote, their prototype that addresses several of these issues.Abstract:Â
Sustainable operation of battery powered wireless embedded systems (such as sensor nodes) is a key challenge, and considerable research effort has been devoted to energy optimization of such systems. Environmental energy harvesting, in particular solar based, has emerged as a viable technique to supplement battery supplies. However, designing an efficient solar harvesting system to realize the potential benefits of energy harvesting requires an in-depth understanding of several factors. For example, solar energy supply is highly time varying and may not always be sufficient to power the embedded system. Harvesting components, such as solar panels, and energy storage elements, such as batteries or ultracapacitors, have different voltage-current characteristics, which must be matched to each other as well as the energy requirements of the system to maximize harvesting efficiency. Further, battery nonidealities, such as self-discharge and round trip efficiency, directly affect energy usage and storage decisions. The ability of the system to modulate its power consumption by selectively deactivating its sub-components also impacts the overall power management architecture. This paper describes key issues and tradeoffs which arise in the design of solar energy harvesting, wireless embedded systems and presents the design, implementation, and performance evaluation of Heliomote, our prototype that addresses several of these issues. Experimental results demonstrate that Heliomote, which behaves as a plug-in to the Berkeley/Crossbow motes and autonomously manages energy harvesting and storage, enables near-perpetual, harvesting aware operation of the sensor node.read more
Citations
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Journal ArticleDOI
Wireless sensor network survey
TL;DR: This survey presents a comprehensive review of the recent literature since the publication of a survey on sensor networks, and gives an overview of several new applications and then reviews the literature on various aspects of WSNs.
Journal ArticleDOI
Energy Harvesting Sensor Nodes: Survey and Implications
TL;DR: Various aspects of energy harvesting sensor systems- architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications are surveyed and the implications of recharge opportunities on sensor node operation and design of sensor network solutions are discussed.
Journal ArticleDOI
Power management in energy harvesting sensor networks
TL;DR: In this paper, the authors have developed abstractions to characterize the complex time varying nature of such sources with analytically tractable models and use them to address key design issues.
Journal ArticleDOI
Energy harvesting in wireless sensor networks: A comprehensive review
TL;DR: A comprehensive taxonomy of the various energy harvesting sources that can be used by WSNs is presented and some of the challenges still need to be addressed to develop cost-effective, efficient, and reliable energy harvesting systems for the WSN environment are identified.
Journal ArticleDOI
Optimal energy management policies for energy harvesting sensor nodes
TL;DR: A greedy policy is identified which, in low SNR regime, is throughput optimal and also minimizes mean delay and two energy management policies which minimize the mean delay in the queue are obtained.
References
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Versatile low power media access for wireless sensor networks
TL;DR: B-MAC's flexibility results in better packet delivery rates, throughput, latency, and energy consumption than S-MAC, and the need for flexible protocols to effectively realize energy efficient sensor network applications is illustrated.
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Geography-informed Energy Conservation for Ad Hoc Routing
TL;DR: In this article, the authors proposed a geographical adaptive fidelity (GAF) algorithm that reduces energy consumption in ad hoc wireless networks by identifying nodes that are equivalent from a routing perspective and turning off unnecessary nodes, keeping a constant level of routing fidelity.
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Low-power CMOS digital design
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Journal ArticleDOI
Energy-aware wireless microsensor networks
TL;DR: This article presents a suite of techniques that perform aggressive energy optimization while targeting all stages of sensor network design, from individual nodes to the entire network.
Proceedings ArticleDOI
Energy aware routing for low energy ad hoc sensor networks
Rahul C. Shah,Jan M. Rabaey +1 more
TL;DR: This paper takes the view that always using lowest energy paths may not be optimal from the point of view of network lifetime and long-term connectivity and proposes a new scheme called energy aware routing that uses sub-optimal paths occasionally to provide substantial gains.